Artifact correction in low‐dose dental CT imaging using Wasserstein generative adversarial networks-Reference-Cited by-同舟云学术

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Artifact correction in low‐dose dental CT imaging using Wasserstein generative adversarial networks

Published:2019-02-14 Issue:4 Volume:46 Page:1686-1696
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Hu Zhanli¹,Jiang Changhui¹²,Sun Fengyi¹,Zhang Qiyang¹,Ge Yongshuai¹,Yang Yongfeng¹,Liu Xin¹,Zheng Hairong¹,Liang Dong¹

Affiliation:

1. Lauterbur Research Center for Biomedical Imaging Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China

2. Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen 518055 China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.13415

Reference51 articles.

1. Computed Tomography and Radiation Risks: What Pediatric Health Care Providers Should Know

2. Computed tomography – an increasing source of radiation exposure;Brenner D;Headache,2008

3. Geometric calibration of a stationary digital breast tomosynthesis system based on distributed carbon nanotube X-ray source arrays

4. Adaptive streak artifact reduction in computed tomography resulting from excessive x-ray photon noise

5. Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography

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